Nonparametric Bayesian Inference in Biostatistics
As chapters in this book demonstrate, BNP has important uses in clinical sciences and inference for issues like unknown partitions in genomics. Nonparametric Bayesian approaches (BNP) play an ever expanding role in biostatistical inference from use in proteomics to clinical trials. Many research problems involve an abundance of data and require flexible and complex probability models beyond the traditional parametric approaches. As this book's expert contributors show, BNP approaches can be the answer. Survival Analysis, in particular survival regression, has traditionally used BNP, but BNP's potential is now very broad. This applies to impor…
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Produktdetails
Weitere Autoren: Müller, Peter (Hrsg.)
- ISBN: 978-3-319-19517-9
- EAN: 9783319195179
- Produktnummer: 31948463
- Verlag: Springer Nature EN
- Sprache: Englisch
- Erscheinungsjahr: 2015
- Seitenangabe: 448 S.
- Masse: H23.5 cm x B15.5 cm 9'066 g
- Auflage: 1st ed. 2015
- Abbildungen: schwarz-weiss Illustrationen, farbige Illustrationen, Tabellen, schwarz-weiss
- Gewicht: 9066
- Sonstiges: Research
Über den Autor
Riten Mitra is Assistant Professor in the Department of Bioinformaticsand Biostatistics at University of Louisville. His research interestsinclude Bayesian graphical models and nonparametric Bayesian methods with a special emphasis on applications in genomics andbioinformatics. Peter Mueller is Professor in the Department of Mathematics and theDepartment of Statistics & Data Science at the University of Texas at Austin. He has published widely on nonparametric Bayesian statistics, with an emphasis on applications in biostatistics and bioinformatics.
2 weitere Werke von Riten (Hrsg.) Mitra:
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